Tag Archives: quantitative data

Actually when it comes to quantitative data, there are 4 levels, but who’s counting? (Besides Goldilocks.)

Nominal (categorical) data are names or categories: (gender, religious affiliation, days of the week, yes or no, and so on)

Ordinal data are like the pain scale. Each number is higher (or lower) than the next but the distances between numbers are not equal. In others words 4 is not necessarily twice as much as 2; and 5 is not half of 10.

Interval data are like degrees on a thermometer. Equal distance between them, but no actual “0”. 0 degrees is just really, really cold.

[After watching video: Note that the variable that is controlled by the researcher is call the Independent variable or Cause variable because it creates a change in something else. That something else that changes is the Dependent variable or Outcome variable.]

CRITICAL THINKING:

Based on the video, can you explain why true experiments are often called randomized controlled trial (RCT)?

If you want to know what someone thinks or feels, you ask them, right?

The same is true in research, but it is good to know the pros and cons of using the “self-report method” of collecting data in order to answer a research question. Most often self-report is done in ‘paper & pencil’ or SurveyMonkey form, but it can be done by interview.

Generally self-report is easy and inexpensive, and sometimes facilitates research that might otherwise be impossible. To answer well, respondents must be honest, have insight into themselves, and understand the questions. Self-report is an important tool in much behavioral research.

But, using self-report to answer a research question does have its limits. People may tend to answer in ways that make themselves look good (social desirability bias), agree with whatever is presented (social acquiescence bias), or answer in either extreme terms (extreme response set bias) or always pick the non-commital middle numbers. Another problem will occur if the reliability and validity of the self-report questionnaire is not established. (Reliability is consistency in measurement and validity is the accuracy of measuring what it purports to measure.) Additionally, self-reports typically provide only a)ordinal level data, such as on a 1-to-5 scale, b) nominal data, such as on a yes/no scale, or c) qualitative descriptions in words without categories or numbers. (Ordinal data=scores are in order with some numbers higher than others, and nominal data = categories. Statistical calculations are limited for both and not possible for qualitative data unless the researcher counts themes or words that recur.)

An example of a self-report measure that we regard as a gold standard for clinical and research data = 0-10 pain scale score. An example of a self-report measure that might be useful but less preferred is a self-assessment of knowledge (e.g., How strong on a 1-5 scale is your knowledge of arterial blood gas interpretation?) The use of it for knowledge can be okay as long as everyone understands that it is perceived level of knowledge.

Critical Thinking: What was the research question in this study? Malaria et al. (2016) Pain assessment in elderly with behavioral and psychological symptoms of dementia. Journal of Alzheimer’s Disease as posted on PubMed.govat http://www.ncbi.nlm.nih.gov/pubmed/26757042with link to full text. How did the authors use self-report to answer their research question? Do you see any of the above strengths & weaknesses in their use?

For more information: Be sure to check out Rob Hoskins blog: http://www.sciencebrainwaves.com/the-dangers-of-self-report/

What is a research hypothesis? A research hypothesis is a predicted answer; an educated guess. It is a statement of the outcome that a researcher expects to find in an experimental study.

Why care? Because it tells you precisely the problem that the research study is about! Either the researcher’s prediction turns out to be true (supported by data) or not!A hypothesis includes 3 key elements: 1) the population of interest, 2) the experimental treatment, & 3) the outcome expected. It is a statement of cause and effect. The experimental treatment that the researcher manipulates is called the independent or cause variable. The result of the study is an outcome that is called the dependent variable because it depends on the independent/cause variable.

For example, let’s take the hypothesis “Heart failure patients who receive experimental drug X will have better cardiac function than will heart failure patients who receive standard drug Y.” You can see that the researcher is manipulating the drug (independent variable) that patients will receive. And patient cardiac outcomes are expected to vary—in fact cardiac function is expected to be better—for patients who receive the experimental drug X.

Ideally that researcher will randomly assign subjects to an experimental group that receives drug X and a control group that receives standard therapy drug Y. Outcome cardiac function data will be collected and analyzed to see if the researcher’s predicted answer (AKA hypothesis) is true.

In a research article, the hypothesis is usually stated right at the end of the introduction or background section.

If you see a hypothesis, how can you tell what is the independent/cause variable and the dependent/effect/outcome variable? 1st – Identify the population in the hypothesis—the population does not vary (& so, it is not a variable). 2nd – Identify the independent variable–This will be the one that is the cause & it will vary. 3rd – Identify the dependent variable–This will be the one that is the outcome & its variation depends on changes/variation in the independent variable.

PRACTICE: What are the population, independent variable(s) & dependent variable(s) in these actual research study titles that reflect the research hypotheses:

Imagine that you are hospitalized and hurting. During hourly rounds the RN reassures you with these words: “We are going to do everything that we can to help keep your pain under control. Your pain management is our number 1 priority. Given your [condition, history, diagnosis, status], we may not be able to keep your pain level at zero. However, we will work very hard with you to keep you as comfortable as possible.” (Alaloul et al, 2015, p. 323).

Study? In 2015 a set of researchers tested effectiveness of the above pain script using 2 similar medical-surgical units in an academic medical center—1 unit was an experimental unit & 1 was a control unit. RNs rounded hourly on both units. On the experimental unit RNs stated the script to patients exactly as written and on room whiteboards posted the script, last pain med & pain scores. Posters of the script were also posted on the unit. In contrast, on the control unit RN communication and use of whiteboard were dependent on individual preferences. Researchers measured effectiveness of the script by collecting HCAHPS scores 2 times before RNs began using the script (a baseline pretest) and then 5 times during and after RNs began using it (a posttest) on both units.

Results? On the experimental units significantly more patients reported that the team was doing everything they could to control pain and that the pain was well-controlled (p≤.05). And while experimental unit scores were trending up, control unit scores trended down. Other findings were that the RNs were satisfied with the script, and that RNs having a BSN or MSN had no effect.

Conclusions/Implications? “When nurses used clear and consistent communication with patients in pain, a positive effect was seen in patient satisfaction with pain management over time. This intervention was simple and effective. It could be replicated in a variety of health care organizations.” (p.321) [underline added]

Commentary: While an experiment would have created greater confidence that the script caused the improvements in patient satisfaction, an experiment would have been difficult or impossible. Researchers could not randomly assign patients to experimental & control units. Still, quasi-experimental research is relatively strong evidence, but it leaves the door open that something besides the script caused the improvements in HCAHPS scores.

Critical thinking? What would prevent you from adopting or adapting this script in your own personal practice tomorrow? What are the barriers and facilitators to getting other RNs on your unit to adopt this script, including using whiteboards? Are there any risks to using the script? What are the risks to NOT using the script?

This is the very 1st section of the body of the research article. In it you will find a description of the problem that the researcher is studying, why the problem is a priority, and sometimes what is already known about the problem. The description of what is already known may or may not be labelled separately as a Review of Literature.

Key point #1: Articles & research that are reviewed in the Intro/Background should be mostly within the past 5-7 years. Sometimes included are classic works that may be much older OR sometimes no recent research exists. If recent articles aren’t used, this should raise some questions in your mind. You know well that healthcare changes all the time!! If there are no recent studies the author should explain.

Key point #2: The last sentence or two in the Intro/Background is the research question or hypothesis. If you need to know the research question/hypothesis right away, you can skip straight to the end of the Intro/background—and there it should be!

Happy research reading!

Critical Thinking: Do the sections of the abstract AND the sections of the research article match above headings? Does it match the description of Introduction? Take a look at the free article by Kennedy et al. (2014). Is there a relationship between personality and choice of nursing specialty: An integrative literature,BMC Nursing, 13(40). Retrieved from the link http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4267136/.

Does the very idea of looking at data make your eyes cross and set your teeth on edge?

If so, I have the solution for you!! And you DO need a solution because Data–>Information–>Best Practices.

You might be surprised that in less than 10 minutes John Hicks at https://www.youtube.com/watch?v=–r9_R60Jws will have you able to describe the basic approach to data. He gives you 4 key steps & builds from there.

I promise: No eyes glazing over. No getting lost in numbers and calculations. No problem. Don’t worry; be happy.

I can feel it. Your research reading skills have gone up a notch! (And for those of you who are masters of data & analysis, enjoy this link for teaching others.)

For more Info: Watch his great follow-up, short, & sweet videos for more on statistics.

CRITICAL THINKING: First watch the video above—click here if you didn’t yet do that. Second outline the 4 steps using the abstract below. Third, answer these questions: Are the data quantitative or qualitative? Are the data are continuous or discrete? Are the data are primary or secondary?

“Background: Nursing has come a long way since the days of Florence Nightingale and even though no consensus exists it would seem reasonable to assume that caring still remains the inner core, the essence of nursing. In the light of the societal, contextual and political changes that have taken place during the 21st century, it is important to explore whether these might have influenced the essence of nursing. The aim of this study was to describe registered nurses’ conceptions of caring. Methods: A qualitative design with a phenomenographic approach was used. The interviews with twenty-one nurses took place between March and May 2013 and the transcripts were analysed inspired by Marton and Booth’s description of phenomenography. Results: The analysis mirrored four qualitatively different ways of understanding caring from the nurses’ perspective: caring as person-centredness, caring as safeguarding the patient’s best interests, caring as nursing interventions and caring as contextually intertwined. Conclusion: The most comprehensive feature of the nurses’ collective understanding of caring was their recognition and acknowledgment of the person behind the patient, i.e. person-centredness. However, caring was described as being part of an intricate interplay in the care context, which has impacted on all the described conceptions of caring. Greater emphasis on the care context, i.e. the environment in which caring takes place, are warranted as this could mitigate the possibility that essential care is left unaddressed, thus contributing to better quality of care and safer patient care.” [quoted from http://www.ncbi.nlm.nih.gov/pubmed/25834478]